Regression Models for the Comparison of Measurement Methods

Heleno Bolfarine is a Full Professor at the Instituto de Matemática e Estatística of the Universidade de São Paulo, SP, Brazil. He received his PhD in Probability and Statistics from the University of California at Berkeley, USA. Prof. Bolfarine has published more than 190 articles in respected ,international, peer-reviewed journals, and co-authored the book "Prediction Theory for Finite Populations", published by Springer. His research focuses on statistical inference, more specifically on mixed models and finite populations. Mário de Castro is an Associate Professor at the Instituto de Ciências Matemáticas e de Computação of the Universidade de São Paulo at São Carlos, SP, Brazil. He completed his PhD studies in Statistics at the Instituto de Matemática e Estatística, Universidade de São Paulo, Brazil, and postdoctoral studies at the University of Connecticut, USA. His research interests include measurement errors, survival analysis and data modeling for counting. He has authored or co-authored more than 60 papers. Manuel Galea is an Associate Professor at the Pontificia Universidad Católica de Chile. He received his PhD in Statistics from the Instituto de Matemática e Estatística, Universidade de São Paulo, Brazil. His fields of research include inference and influence diagnosis in measurement error models under elliptical distributions. Dr. Galea has published more than 70 papers, as author or co-author.

- Introduction.- Two Methods.- Two or More Methods.- Model Checking and Influence Assessment.- Data Analysis.- Miscellaneous Results.- R Scripts.- Index.

"This book is a successful compilation of such developments in the last two decades and presents them concisely to help researchers and practitioners. ... The book requires the reader to have a solid background in mathematical statistics and detailed knowledge of areas such as measurement error models. It also provides a platform for new entrants in this area to begin their research with complete references and updated developments in one place." (Shalabh, Mathematical Reviews, April, 2022)

“This book is a successful compilation of such developments in the last two decades and presents them concisely to help researchers and practitioners. … The book requires the reader to have a solid background in mathematical statistics and detailed knowledge of areas such as measurement error models. It also provides a platform for new entrants in this area to begin their research with complete references and updated developments in one place.” (Shalabh, Mathematical Reviews, April, 2022)